Research Assistant Professor in Machine learning for Crystallographic Method Development Full-time

Researcher Position

We are looking for a highly motivated and dynamic researcher for a 46-months position to start as soon as possible. This position will be part of the Research Project “Deep Learning Accelerated Crystallographic Pipeline” financed by the Novo Nordisk Foundation to Associate Professor Anders Østergaard Madsen.

The Department of Pharmacy at the University of Copenhagen is devoted to research and research-based teaching in drug formulation and manufacturing, drug-related analytical and physical chemistry, drug metabolism, chemical toxicology and medicines use. The Department plays a key role in advancing the pharmaceutical sciences in Denmark and internationally.

Our research group Pharmaceuticals, Products and Processes (3P) is focusing on innovative pharmaceutical product design, as well as defined aspects of materials science (solid state structure and rheology). The 3P group has a highly international profile with approximately 20 members and an average annual scientific productivity at around 40 international scientific peer-reviewed papers. This research area has also attracted several industrial co-operation projects, and we actively co-operate with several Danish and international fine chemical companies.

Your job

You will play a central role in the Novo Nordisk Foundation–funded project Deep Learning–Accelerated Crystallographic Pipeline, which aims to integrate supervised machine‑learning models into a modular, open‑source workflow for small‑molecule crystallography. The position focuses on method development rather than application.

Your primary responsibilities will include:

• Developing deep‑learning approaches for central crystallographic challenges.
• Designing, generating, and curating large-scale simulated datasets, including diffraction, electron density, and disorder models, for training and validating ML architectures.
• Designing ML modules for integration in a modular crystallographic pipeline enabling seamless interaction between traditional algorithms and new deep‑learning components.
• Collaborating closely with key partners at Durham University (mathematical crystallography) and at the MAX IV synchtrotron (SINCRYS beamline).
• Contributing to high‑impact publications, open‑source software releases, and dissemination of method developments within the crystallographic community.

This position is heavily research‑driven, with substantial freedom to pursue methodological innovations within the scope of the project.

Profile

We seek an exceptionally strong candidate with a clear track record at the interface of crystallography, computation, and machine learning. The ideal applicant will have the following essential qualifications:

• A PhD in chemistry, physics, materials science, crystallography, or a closely related discipline.
• Demonstrable expertise in small‑molecule crystallography.
• Substantial experience with deep learning applied to scientific or physical data, including development, training, and evaluation of neural networks.
• Documented experience with large synthetic or simulated datasets (e.g., diffraction simulations, MD‑generated models).
• Strong programming proficiency, including experience with numerical and GPU‑accelerated workflows.
• Excellent written and oral communication skills, and the ability to work collaboratively in a multidisciplinary team.

Desirable experience and skills:

• Experience in data‑driven method development, such as model validation, benchmarking, and analytical comparison with established crystallographic algorithms.
• Experience in modelling molecular systems using force-field based and ab-initio methods.
• A strong publication record in crystallography, machine learning, computational chemistry, or related areas.

Place of employment

The place of employment is at the Department of Pharmacy, University of Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment. Our research facilities include modern laboratories, including diffractometers and a high-performance computing environment.

Terms of employment

The employment as research assistant professor is a full time and fixed-term position for 46 months. Starting date is 1 August 2026 or as soon as possible thereafter.

Salary, pension and terms of employment will be in accordance with the agreement between the Danish Ministry of Finance and AC (Danish Confederation of Professional Associations). Currently, the monthly salary starts at 41,300 DKK/ approx. 5,530 Euro (November 2025-level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18.07 % to your pension fund.

Non-Danish and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

The position is covered by the “Memorandum on Job Structure for Academic Staff at the Universities” of June 28, 2013.

Questions

For further information please contact Anders Østergaard Madsen; a.madsen@sund.ku.dk.

Application procedure

Your online application must be submitted in English by clicking 'Apply for position' below. Furthermore your application must include the following documents/attachments – all in PDF format:

• Motivated letter of application (max. one page).
• CV incl. education, work/research experience, language skills and other skills relevant for the position.
• A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do.
• List of publications.

Application deadline: 15 May 2026, 23.59pm CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

Interviews are expected to be held in week 24.

University of Copenhagen wish to reflect the diversity of society and welcome applications from all qualified candidates regardless of age, disability, gender, nationality, race, religion or sexual orientation. Appointment will be based on merit alone.